Table of Contents

Foreword
Introduction
1 Scope
2 Normative references
3 Terms and definitions
4 Conventions and notation
5 Principles of straight-line calibration
6 Model for uncertainties associated with the y[i]
7 Model for uncertainties associated with the x[i] and
   the y[i]
8 Model for uncertainties associated with the x[i] and
   the y[i] and covariances associated with the pairs
   (x[i], y[i])
9 Model for uncertainties and covariances associated
   with the y[i]
10 Model for uncertainties and covariances associated
   with the x[i] and the y[i]
11 Use of the calibration function
Annexes
Annex A (informative) - Matrix operations
Annex B (informative) - Application of the Gauss-Newton
        algorithm to generalized distance regression
Annex C (informative) - Orthogonal factorization approach
        to solving the generalized Gauss-Markov problem
Annex D (informative) - Provision of uncertainties and
        covariances associated with the measured x- and
        y-values
Annex E (informative) - Uncertainties known up to a scale
        factor
Annex F (informative) - Software implementation of
        described algorithms
Annex G (informative) - Glossary of principal symbols
Bibliography

Abstract

Defines the use of the calibration function parameter estimates and their associated uncertainties and covariance to predict a value of X and its associated standard uncertainty given a measured value of Y and its associated standard uncertainty.

General Product Information

Published
Document Type	Standard
Status	Current
Publisher	International Organization for Standardization
Pages
ISBN
Committee	TC 69